{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5db8f8bf-a0dd-4e3a-b650-c32632a1a320",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from sklearn.tree import DecisionTreeClassifier, plot_tree\n",
    "from sklearn.metrics import (\n",
    "    accuracy_score, confusion_matrix, classification_report,\n",
    "    roc_auc_score, roc_curve,auc\n",
    ")\n",
    "import joblib\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "warnings.simplefilter('ignore')\n",
    "# 设置中文字体\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 设置中文字体为黑体"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7f19a39-8359-4cd1-a188-919cbd29983d",
   "metadata": {},
   "source": [
    "# 1、读数据 简单了解"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4f5eea9d-24dc-4d6d-aa9c-c4c04516716a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取数据\n",
    "df = pd.read_csv('优惠券核销数据.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "402fddc1-e1fc-4bf8-a81f-18508c931ca6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据前5行：\n",
      "    Accepted  Sex  Age  Class  AvgSpending\n",
      "0         0    2    1      1           38\n",
      "1         0    1    1      1           33\n",
      "2         0    2    1      1           37\n",
      "3         0    2    1      1           40\n",
      "4         0    2    1      1           34\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 5 columns):\n",
      " #   Column       Non-Null Count  Dtype\n",
      "---  ------       --------------  -----\n",
      " 0   Accepted     891 non-null    int64\n",
      " 1   Sex          891 non-null    int64\n",
      " 2   Age          891 non-null    int64\n",
      " 3   Class        891 non-null    int64\n",
      " 4   AvgSpending  891 non-null    int64\n",
      "dtypes: int64(5)\n",
      "memory usage: 34.9 KB\n",
      "\n",
      "数据基本信息：\n",
      " None\n",
      "\n",
      "描述性统计：\n",
      "          Accepted         Sex         Age       Class  AvgSpending\n",
      "count  891.000000  891.000000  891.000000  891.000000   891.000000\n",
      "mean     0.616162    1.352413    1.674523    1.691358    59.132435\n",
      "std      0.486592    0.477990    0.468816    0.836071    45.776231\n",
      "min      0.000000    1.000000    1.000000    1.000000    22.000000\n",
      "25%      0.000000    1.000000    1.000000    1.000000    38.000000\n",
      "50%      1.000000    1.000000    2.000000    1.000000    44.000000\n",
      "75%      1.000000    2.000000    2.000000    2.000000    62.000000\n",
      "max      1.000000    2.000000    2.000000    3.000000   529.000000\n",
      "\n",
      "核销分布（0未核销，1核销）：\n",
      " Accepted\n",
      "1    549\n",
      "0    342\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 数据探索\n",
    "print(\"数据前5行：\\n\", df.head())\n",
    "print(\"\\n数据基本信息：\\n\", df.info())\n",
    "print(\"\\n描述性统计：\\n\", df.describe())\n",
    "print(\"\\n核销分布（0未核销，1核销）：\\n\", df['Accepted'].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49c8dd23-85d1-4f79-aecd-02b519dc13c0",
   "metadata": {},
   "source": [
    "# 2、数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "27f908e7-8b61-46cf-8542-7dc0f763e203",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accepted       0\n",
      "Sex            0\n",
      "Age            0\n",
      "Class          0\n",
      "AvgSpending    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#查看缺失值\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "404af5f5-ed28-472c-8819-c61dd3bd98a2",
   "metadata": {},
   "source": [
    "# 3、切分数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d038ca3c-b527-447b-aeea-4e0146156b3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 分类变量独热编码（Sex, Age, Class）\n",
    "X = df.drop('Accepted', axis=1)\n",
    "y = df['Accepted']\n",
    "X_encoded = pd.get_dummies(X, columns=['Sex', 'Age', 'Class'], drop_first=True)\n",
    "\n",
    "# 划分数据集\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X_encoded, y, test_size=0.3, random_state=42\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16e9e4d7-b872-4c79-a48e-c59f8b22c6b7",
   "metadata": {},
   "source": [
    "# 4、确认最优k值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "071f0a4e-a3f0-4dbc-b0bc-5309b9b9da16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "深度最优（基于交叉验证）: 3\n",
      "对应的交叉验证 AUC: 0.8374\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "# 确定最优树深度（Max Depth）可视化\n",
    "max_depths = range(1, 16)\n",
    "train_scores = []\n",
    "cv_scores = []\n",
    "test_scores = []\n",
    "\n",
    "for depth in max_depths:\n",
    "    dt = DecisionTreeClassifier(max_depth=depth, random_state=42)\n",
    "    \n",
    "    # 训练集分数\n",
    "    dt.fit(X_train, y_train)\n",
    "    train_scores.append(roc_auc_score(y_train, dt.predict_proba(X_train)[:, 1]))\n",
    "    \n",
    "    # 交叉验证分数\n",
    "    cv_scores.append(np.mean(cross_val_score(dt, X_train, y_train, cv=5, scoring='roc_auc')))\n",
    "    \n",
    "    # 测试集分数\n",
    "    test_scores.append(roc_auc_score(y_test, dt.predict_proba(X_test)[:, 1]))\n",
    "\n",
    "# 绘制结果\n",
    "plt.figure(figsize=(12, 8))\n",
    "plt.plot(max_depths, train_scores, label='Train AUC')\n",
    "plt.plot(max_depths, cv_scores, label='CV AUC')\n",
    "plt.plot(max_depths, test_scores, label='Test AUC')\n",
    "plt.xlabel('Max Depth')\n",
    "plt.ylabel('ROC AUC')\n",
    "plt.title('决策树深度选择分析（带交叉验证）')\n",
    "plt.axvline(x=np.argmax(cv_scores) + 1, color='r', linestyle='--', label='Optimal Depth (CV)')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "print(f\"深度最优（基于交叉验证）: {np.argmax(cv_scores) + 1}\")\n",
    "print(f\"对应的交叉验证 AUC: {np.max(cv_scores):.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6c576b0-2fb7-4a6b-9a68-41027759ba4f",
   "metadata": {},
   "source": [
    "# 5、决策树模型训练与可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "12c32fd7-9b8a-4794-bd5f-34059169f2bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(max_depth=3, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(max_depth=3, random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeClassifier(max_depth=3, random_state=42)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_depth = 3\n",
    "best_dt = DecisionTreeClassifier(max_depth=best_depth, random_state=42)\n",
    "best_dt.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1eb92b8f-0094-493a-8613-200e55950330",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import plot_tree\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 可视化决策树\n",
    "plt.figure(figsize=(20, 10))  # 设置图形大小\n",
    "plot_tree(best_dt, \n",
    "          feature_names=X_train.columns,  # 特征名称（如果 X_train 是 DataFrame）\n",
    "          class_names=best_dt.classes_.astype(str),  # 类别名称\n",
    "          filled=True,  # 节点填充颜色\n",
    "          rounded=True,  # 圆角显示\n",
    "          fontsize=10)  # 字体大小\n",
    "plt.title(\"Decision Tree Visualization\")  # 添加标题\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b22dbc30-ac6b-4e27-ba70-e144433a1a22",
   "metadata": {},
   "source": [
    "# 6、特征的重要性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "e98965ae-5c0f-4e79-8f52-38d9f2924cca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 特征重要性分析\n",
    "features = pd.Series(best_dt.feature_importances_, index=X_encoded.columns)\n",
    "features = features.sort_values(ascending=False)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.barplot(x=features.values, y=features.index, palette='viridis')\n",
    "plt.title('特征重要性排序')\n",
    "plt.xlabel('Importance')\n",
    "plt.ylabel('Features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd4365f7-5e84-457c-8cdd-82d4294d4532",
   "metadata": {},
   "source": [
    "# 7、评价模型 混淆矩阵 ROC AUC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "1b96cddd-91e3-494e-b168-9b4b696eeefb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "准确率: 0.7798507462686567\n",
      "分类报告:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.68      0.70      0.69        94\n",
      "           1       0.84      0.82      0.83       174\n",
      "\n",
      "    accuracy                           0.78       268\n",
      "   macro avg       0.76      0.76      0.76       268\n",
      "weighted avg       0.78      0.78      0.78       268\n",
      "\n",
      "ROC AUC: 0.8137686475910981\n"
     ]
    }
   ],
   "source": [
    "#评价模型\n",
    "y_pred_dt= best_dt.predict(X_test)\n",
    "y_proba_dt= best_dt.predict_proba(X_test)[:, 1]\n",
    "\n",
    "print(\"准确率:\", accuracy_score(y_test, y_pred))\n",
    "print(\"分类报告:\\n\", classification_report(y_test, y_pred))\n",
    "print(\"ROC AUC:\", roc_auc_score(y_test, y_proba))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "93762d9d-1ffb-4ba6-8365-b9c6dd3d6c7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 混淆矩阵\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues',\n",
    "            xticklabels=['未核销', '核销'],\n",
    "            yticklabels=['未核销', '核销'])\n",
    "plt.title('混淆矩阵')\n",
    "plt.ylabel('真实值')\n",
    "plt.xlabel('预测值')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "299b94b4-8859-4cd2-bdc7-4e4e0f62e2e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ROC曲线\n",
    "fpr, tpr, _ = roc_curve(y_test, y_proba)\n",
    "plt.plot(fpr, tpr, label=f'AUC = {roc_auc_score(y_test, y_proba):.2f}')\n",
    "plt.plot([0, 1], [0, 1], 'k--')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('ROC曲线')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f15055e6-9fdb-427b-8016-95c27190650d",
   "metadata": {},
   "source": [
    "# 8、保存模型进行预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "dea490f8-40b0-4394-92d6-39c06ee968de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型已保存为 'best_decision_tree_model.pkl'\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "\n",
    "# 保存模型\n",
    "with open('best_decision_tree_model.pkl', 'wb') as file:\n",
    "    pickle.dump(best_dt, file)\n",
    "\n",
    "print(\"模型已保存为 'best_decision_tree_model.pkl'\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "094a57bc-1ece-4a71-a0c7-ff51b8056301",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型已加载\n",
      "高概率客户数量：433（占比48.6%）\n"
     ]
    }
   ],
   "source": [
    "# 加载模型\n",
    "with open('best_decision_tree_model.pkl', 'rb') as file:\n",
    "    model = pickle.load(file)\n",
    "\n",
    "print(\"模型已加载\")\n",
    "\n",
    "# 加载数据\n",
    "df = pd.read_csv('优惠券核销数据.csv')\n",
    "X = pd.get_dummies(df.drop('Accepted', axis=1), \n",
    "                 columns=['Sex', 'Age', 'Class'], drop_first=True)\n",
    "\n",
    "# 预测全量数据\n",
    "df['Predicted'] = model.predict(X)\n",
    "df['Probability'] = model.predict_proba(X)[:, 1]  # 核销概率\n",
    "\n",
    "high_prob_customers = df[df['Probability'] >= 0.75].copy()\n",
    "high_prob_customers.to_csv('高核销概率客户名单.csv', index=False)\n",
    "\n",
    "print(f\"高概率客户数量：{len(high_prob_customers)}（占比{len(high_prob_customers)/len(df):.1%}）\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "57be02d1-196b-400b-8f0d-28c166c55690",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "sns.boxplot(x='Accepted', y='AvgSpending', data=df)\n",
    "plt.title('核销/未核销客户消费额分布对比')\n",
    "plt.xticks([0, 1], ['未核销', '核销'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "97d83ea4-d95c-40cc-a7e4-1ff1ff977a0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross_tab = pd.crosstab(df['Class'], df['Accepted'], normalize='index')*100\n",
    "cross_tab.plot(kind='bar', stacked=True, figsize=(10, 6))\n",
    "plt.title('不同品类客户的核销比例')\n",
    "plt.ylabel('百分比 (%)')\n",
    "plt.xticks([0, 1, 2], ['低端', '中档', '高端'], rotation=0)\n",
    "plt.legend(title='核销情况', labels=['未核销', '已核销'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "50625ba7-93f5-4ba2-bef3-205ef0232caf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1, 3, 1)\n",
    "gender_accept = df.groupby('Sex')['Accepted'].mean()\n",
    "sns.barplot(x=['女', '男'], y=gender_accept, palette=['salmon', 'steelblue'])\n",
    "plt.title('性别核销率对比')\n",
    "plt.ylabel('核销率')\n",
    "plt.ylim(0, 1)\n",
    "for i, v in enumerate(gender_accept):\n",
    "    plt.text(i, v+0.03, f\"{v:.1%}\", ha='center')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "ad4aff22-2ec1-43ca-b656-aea889a80743",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1f25f080d70>"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#性别与品类核销率\n",
    "plt.subplot(1, 3, 2)\n",
    "sns.pointplot(x='Class', y='Accepted', hue='Sex', data=df,\n",
    "             palette=['salmon', 'steelblue'], markers=['o', 's'])\n",
    "plt.title('性别-品类核销率趋势')\n",
    "plt.xticks([0, 1, 2], ['低端', '中档', '高端'])\n",
    "plt.ylabel('核销率')\n",
    "plt.legend(title='性别')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4adfcdfa-5661-4d09-94b1-6e9fdabd6d7a",
   "metadata": {},
   "source": [
    "# 9、其他模型建立"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "41c44770-35d7-4800-89f5-5d9f4dba7f17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "随机森林最佳参数: {'criterion': 'gini', 'max_depth': 5, 'min_samples_split': 2, 'n_estimators': 200}\n",
      "随机森林测试集 AUC: 0.8291\n",
      "\n",
      "分类报告:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.76      0.66      0.70        94\n",
      "           1       0.83      0.89      0.86       174\n",
      "\n",
      "    accuracy                           0.81       268\n",
      "   macro avg       0.79      0.77      0.78       268\n",
      "weighted avg       0.80      0.81      0.80       268\n",
      "\n",
      "\n",
      "混淆矩阵:\n",
      "[[ 62  32]\n",
      " [ 20 154]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import roc_auc_score, classification_report, confusion_matrix\n",
    "\n",
    "# 定义随机森林模型\n",
    "rf = RandomForestClassifier(random_state=42)\n",
    "\n",
    "# 定义参数网格\n",
    "param_grid = {\n",
    "    'n_estimators': [50, 100, 200],\n",
    "    'max_depth': [3, 5, 7, None],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    'criterion': ['gini', 'entropy']\n",
    "}\n",
    "\n",
    "# 使用网格搜索进行超参数优化\n",
    "grid_search = GridSearchCV(rf, param_grid, scoring='roc_auc', cv=5)\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "# 获取最佳模型\n",
    "best_rf = grid_search.best_estimator_\n",
    "\n",
    "# 评估模型\n",
    "y_pred_rf = best_rf.predict(X_test)\n",
    "y_proba_rf = best_rf.predict_proba(X_test)[:, 1]\n",
    "\n",
    "print(\"随机森林最佳参数:\", grid_search.best_params_)\n",
    "print(f\"随机森林测试集 AUC: {roc_auc_score(y_test, y_proba_rf):.4f}\")\n",
    "print(\"\\n分类报告:\")\n",
    "print(classification_report(y_test, y_pred_rf))\n",
    "print(\"\\n混淆矩阵:\")\n",
    "print(confusion_matrix(y_test, y_pred_rf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8b1c0338-3144-4f22-9fcc-b586f324282c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SVM 最佳参数: {'svc__C': 0.1, 'svc__gamma': 'scale', 'svc__kernel': 'rbf'}\n",
      "SVM 测试集 AUC: 0.8278\n",
      "\n",
      "分类报告:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.70      0.67      0.68        94\n",
      "           1       0.83      0.84      0.84       174\n",
      "\n",
      "    accuracy                           0.78       268\n",
      "   macro avg       0.76      0.76      0.76       268\n",
      "weighted avg       0.78      0.78      0.78       268\n",
      "\n",
      "\n",
      "混淆矩阵:\n",
      "[[ 63  31]\n",
      " [ 27 147]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.pipeline import make_pipeline\n",
    "\n",
    "# 定义支持向量机模型\n",
    "svm = make_pipeline(StandardScaler(), SVC(probability=True, random_state=42))\n",
    "\n",
    "# 定义参数网格\n",
    "param_grid = {\n",
    "    'svc__C': [0.1, 1, 10],\n",
    "    'svc__kernel': ['linear', 'rbf', 'poly'],\n",
    "    'svc__gamma': ['scale', 'auto']\n",
    "}\n",
    "\n",
    "# 使用网格搜索进行超参数优化\n",
    "grid_search = GridSearchCV(svm, param_grid, scoring='roc_auc', cv=5)\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "# 获取最佳模型\n",
    "best_svm = grid_search.best_estimator_\n",
    "\n",
    "# 评估模型\n",
    "y_pred_svm = best_svm.predict(X_test)\n",
    "y_proba_svm = best_svm.predict_proba(X_test)[:, 1]\n",
    "\n",
    "print(\"SVM 最佳参数:\", grid_search.best_params_)\n",
    "print(f\"SVM 测试集 AUC: {roc_auc_score(y_test, y_proba_svm):.4f}\")\n",
    "print(\"\\n分类报告:\")\n",
    "print(classification_report(y_test, y_pred_svm))\n",
    "print(\"\\n混淆矩阵:\")\n",
    "print(confusion_matrix(y_test, y_pred_svm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f3be91bd-7fdc-4e29-8601-8e7d2d8057e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "逻辑回归最佳参数: {'logisticregression__C': 0.1, 'logisticregression__penalty': 'l2', 'logisticregression__solver': 'saga'}\n",
      "逻辑回归测试集 AUC: 0.8094\n",
      "\n",
      "分类报告:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.70      0.67      0.68        94\n",
      "           1       0.83      0.84      0.84       174\n",
      "\n",
      "    accuracy                           0.78       268\n",
      "   macro avg       0.76      0.76      0.76       268\n",
      "weighted avg       0.78      0.78      0.78       268\n",
      "\n",
      "\n",
      "混淆矩阵:\n",
      "[[ 63  31]\n",
      " [ 27 147]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "# 定义逻辑回归模型\n",
    "lr = make_pipeline(StandardScaler(), LogisticRegression(random_state=42))\n",
    "\n",
    "# 定义参数网格\n",
    "param_grid = {\n",
    "    'logisticregression__C': [0.1, 1, 10, 100],\n",
    "    'logisticregression__penalty': ['l1', 'l2'],\n",
    "    'logisticregression__solver': ['liblinear', 'saga']\n",
    "}\n",
    "\n",
    "# 使用网格搜索进行超参数优化\n",
    "grid_search = GridSearchCV(lr, param_grid, scoring='roc_auc', cv=5)\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "# 获取最佳模型\n",
    "best_lr = grid_search.best_estimator_\n",
    "\n",
    "# 评估模型\n",
    "y_pred_lr = best_lr.predict(X_test)\n",
    "y_proba_lr = best_lr.predict_proba(X_test)[:, 1]\n",
    "\n",
    "print(\"逻辑回归最佳参数:\", grid_search.best_params_)\n",
    "print(f\"逻辑回归测试集 AUC: {roc_auc_score(y_test, y_proba_lr):.4f}\")\n",
    "print(\"\\n分类报告:\")\n",
    "print(classification_report(y_test, y_pred_lr))\n",
    "print(\"\\n混淆矩阵:\")\n",
    "print(confusion_matrix(y_test, y_pred_lr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "65a23ede-fa14-4a7b-a0e3-14dfb2543094",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "模型 AUC 对比:\n",
      "Decision Tree: 0.8138\n",
      "Random Forest: 0.8291\n",
      "SVM: 0.8278\n",
      "Logistic Regression: 0.8094\n",
      "\n",
      "最佳模型: Random Forest (AUC: 0.8291)\n"
     ]
    }
   ],
   "source": [
    "# 模型名称和对应的预测概率\n",
    "models = {\n",
    "    'Decision Tree': y_proba_dt,\n",
    "    'Random Forest': y_proba_rf,\n",
    "    'SVM': y_proba_svm,\n",
    "    'Logistic Regression': y_proba_lr,\n",
    "}\n",
    "\n",
    "# 计算每个模型的 AUC\n",
    "auc_scores = {name: roc_auc_score(y_test, y_proba) for name, y_proba in models.items()}\n",
    "\n",
    "# 打印 AUC 分数\n",
    "print(\"模型 AUC 对比:\")\n",
    "for name, auc in auc_scores.items():\n",
    "    print(f\"{name}: {auc:.4f}\")\n",
    "\n",
    "# 选择最佳模型\n",
    "best_model_name = max(auc_scores, key=auc_scores.get)\n",
    "print(f\"\\n最佳模型: {best_model_name} (AUC: {auc_scores[best_model_name]:.4f})\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "034b1fe3-2bff-4775-bead-376e8c3cb033",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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